You will be given a definition of a task first, then some input of the task.
In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

In this work, we propose to generate unanswerable questions by editing an answerable question and conditioning on the corresponding paragraph that contains the answer. So the generated unanswerable questions are more lexically similar and relevant to the context. Moreover, by using the answerable question as a prototype and its answer span as a plausible answer, the generated examples can provide more discriminative training signal to the question answering model. 
 Question: Does their approach require a dataset of unanswerable questions mapped to similar answerable questions?
Output:
Yes